tv The Communicators CSPAN January 2, 2017 9:57pm-10:49pm EST
you get from people riding in the car with you? raj: the typical reaction is one of anxiety and angst. fear and occasionally even panic attacks. but then they basically watch the vehicle is able to drive, exactly stopping when it should stop. it's actually riding fairly comfortably with a degree of comfort. peter: we learn more about the move to self-driving cars and professor raj rajkumar at the lab where his experimental car is kept and worked on. dr. raj rajkumar, what's your job here at carnegie mellon? raj: i'm a professor of electric engineering and robotics at carnegie mellon. peter: how'd you get into that? raj: i did my post graduate
studies and got my masters at carnegie mellon. then i left c.m.u. joined i.b.m. research for three years or so and i came back to c.m.u. because i liked c.m.u. and pittsburgh that much. peter: what kind of things do you work on? raj: i work on what are called embedded systems, the technical term. these are things that embed computers inside them but the user basically uses different devices. for example, your smart phone is a sophisticated device but you don't worry about the components inside there. televisions, for example, it has a computer inside it but it is meant to be a television. think about a projector. it.as a computer inside of that toaster that we use on a
daily basis that cost $10, it has a tiny computer embedded inside it. these are embedded systems that act smart but it's a dedicated device of some other kind. i've been working on embedded systems since my doctorate and it turns out vehicles that drive themselves are a classical example of embedded systems. so a car is a car that transports people and goods from point a to point b with components embedded inside them. peter: how did you get into the business of autonomous vehicles? raj: great question. i've been working with general motors, the carmaker since 2004. general motors has been working with the researchers in our department since the year 2000.
i started implying my expertise into embedded systems in the automobile. in 2006, the research advanced by the agency, the research arm of the u.s. military announced a competition. the competition was the -- urban challenge. for vehicles that drive themselves, because anybody in the car, they need to drive for about 60 miles in fewer than six hours. in an urban-like setting, with other self-driving vehicles as well as human driven vehicles and following the same rules of the road that you and i have to follow on a deal he basis. with that competition g.m. became our biggest sponsor. we had about 20 other sponsors but g.m. was the biggest of them. because i already had a strong working relationship with g.m., i became an integral part of the
team that worked on the vehicle, which ended up winning the competition and the $2 million prize. when our team from carnegie mellon won the competition, g.m., who was the biggest sponsor of the team, said hey, our team actually sponsored the winning team and they said because it is about urban driving, a clearly has implications to the consumer market segment and they started a second lab on campus focused exclusively on automated driving and i've been running that plan -- that lab as well since its launch. so our relationship with g.m. continues to be extremely strong and very loyal. peter: so, does g.m. own the technology that you develop?
raj: for the technology that they sponsor -- we're grateful for their support -- but it is actually owned by caron darn -- owned by carnegie mellon university and we have some licensing agreements with g.m. peter: and we learned more about the experimental cadillac as we got ready to take it for a drive. what is this monitor that's up here in the top? raj: that is one of six laser sensors. there's one in the front of the car. there's one in the bumper here. right there. that's the second radar, that's the third on the other side of the bumper as well. there's one behind the side back window of the car and there is one on the other side exactly opposite that. peter: what are they reading? raj: what they are doing is they're sending out multiple laser beams and when the beams basically hit the on the, they bounce back and come back to the
transmitter and because we know the speed of light, we can actually calculate how far that vehicle is. because there are multiple beams scanning as well, you can get a profile of the object. and because we have radar all over the car, it shows what's happening around the vehicle in real-time. peter: is this car communicating with anybody but itself? anybody but itself? raj: it's capable of actually communicating with properly andpped traffic lights similar radios. it's a -- automated vehicle. t.a.v. in short. peter: i also see some cameras inside the car up here. what are these? raj: we had six laser sensors.
three cameras and six radars as well. two camera, one is inside the cabin. one is actually pointed downwards looking for lane markers on the road. the other looks at traffic lights so you know the status of the traffic light. the third camera at the back of the vehicle is for backing purposes, you can see what's going on. and there are also six radars. there's actually one behind this cadillac emblem. we replaced the metal logo with a plastic logo so the radar can see through the plastic. there's one a radar that's behind the bumper. the bumper is made of plastic so the radar can see through the plastic as well. there's another radar on the other side of the bumper and there are two on the side but you cannot see from the outside.
internally they're enclosed. you don't see from the inside either. there's radar at the back in a plastic bumper also. peter: is this car seeing 360 degrees? raj: it is seeing 360 degrees all the time, as opposed to humans, who have to turn our heads around. peter: so, professor, when you get in this car, what's different in the look than a regular cadillac? raj: we tried to make this car look normal on the outside and the inside. on the inside it pretty much operates and looks like a normal car. just like you would rent a car at an airport and pick up the keys, and the layout looks slightly different but we're still able to drive. it's basically the same thing. you bring in your keys, get the
the echo going manually -- vehicle running manually and start driving. looking at the dark board there are two things that have changed. a button on the dashboard, an emergency stop and there's a button behind the stick shift. think of this as the autonomy equivalent of cruise control engage button. so you would actually engage this button to go into autonomous driving mode. so what you need to do is rotate this switch and then pull it upwards to get into autonomous driving mode and that is a very conscious action on the driver's part. peter: is this car licensed to drive the streets of pennsylvania? raj: in pennsylvania, the laws allow a vehicle to drive itself as long as two conditions are satisfied. number one, a licensed human driver in the driver's seat, and number two, that human can take over control at any point in time. on those two conditions, vehicles can drive themselves on pennsylvania public roads.
peter: but this could drive as a normal car as well, correct? raj: of course. this autonomous board, you reflexively push this down. but you would not have the time to do that, you could grab the steering wheel, turn it and press the brake pedals or the gas pedal and the vehicle would still respond. something could be happening that allows the human to take over. and then this button here is only for strictly emergency purposes because we added a bunch of sensors, computers and motors to the vehicle and then in case something totally unexpected happens like you start smelling smoke, you have no idea what is going on, you just push the button and it mechanically, electronically stops the car at that point in
time. knock on wood, we haven't had to engage that when driving yet. peter: what's the cost of all time. the different systems that you're added to this car? raj: many of the sensors, cameras we use are one-off units, they tend to be expensive. so, it is an expensive vehicle because of that. the real idea to be thinking about is that when the volumes go up, the costs will go down significantly. i guess our thinking is that when these vehicles are mass produced, it would add about $5000 extra on top of the cost. but we think he will be very affordable to many people. peter: you're going to give us a driverless ride. is it truly driverless? is that fair to say? raj: it is an automated vehicle. it can drive itself under many conditions but not all conditions yet. not yet. so let's start driving.
i guess i'll take you and i'll explain a few more things. peter: and you're driving manually. raj: i'm driving manually. it says manual on the screen. i'll point out a few things on the screen. it tells us that the screen -- interfaces to the same thing. so i guess if i flip back and forth. this is a screen that we added. by flipping a switch you can go back and forth. peter: what are these images we're seeing here? raj: this is the display which shows what the vehicle is doing at any point in time, so we as humans can be comfortable that the vehicle is indeed doing the right thing.
so what we see here is some icons here, and the icons for example say that i can actually launch, i can stop. i can tell the vehicle to go to the airport, go home or go to work. and this basically lets you zoom in or zoom out. and what you see on the screen is you see two blue lines. they represent the lane the vehicle can drive in. peter: there are no lines on this parking lot we're in. raj: we have programmed the map for this parking lot that allows to us drive along these lanes and we go to the main public roads. that represents the map that your g.p.s. has. the blue line represents the map. then you see a green line there. all the people who basically
ride around this park next to where we are. your g.p.s. device calculates. the g.p.s. has a built-in map database. you as a user punch in your destination. you also see a very short red line up there. that is basically the car knowing the green line route, knowing the blue line maps. it basically uses its sensory data from the radar cameras and basically says for the next 15, 20 meters, this is how, where, i'm going to drive. peter: dr. rajkumar, did you have to program every route ahead of time? or it -- orchid and go on a street it has never been on before? raj: it needs to have a map of the roads. peter: a g.p.s. map. would that count? raj: you can think of this as a g.p.s. map, g.p.s. navigation device and then you tell the system where you want to go.
it uses your navigation and your calculation for the route. just like a garmin device or google maps. and the red line is what the vehicle is deciding in real time. the red line. and so now you'll see if i zoom back a little bit. you see a bunch of dots on the screen. those dots are the laser point from the laser sensors updating in real time. so what you see here is basically a bunch of yellow dots. peter: is that that white car? raj: that's the white car. these dark navy blue colors is the dumpster there. and you basically see a -- peter: and all these white lines are the trees. ok. basically the car consents ther can sense --
radars and cameras and lasers act as the eyes and ears of the vehicle. peter: how far can it see? raj: 775 meters. it has built-in wireless communications radios that can go as far as 600 meters. peter: all right. raj: so let's engage the vehicle in autonomous mode. i'm going to do the following. the vehicle is in parking mode. i'm going to engage autonomous mode. peter: while it's in park? raj: while it's in park. >> autonomous driving. peter: it started driving. does it ever make you nervous? raj: i guess the normal reaction for anybody new at this is to feel anxiety and anxious -- and angst.
it's a very normal reaction but let's see how the vehicle does. peter: ok. dallas, you doing ok back there? dallas: i think so. peter: and it turns on its turn signals. because you told it where you wanted to go already, correct? raj: yes. peter: ok. all right. so you hit the brakes? raj: i did not. breaks?h, it hit the and it knows the speed limit. raj: even though the legal speed limit is 25, pretty much everybody drives at 35 or 40. but this is a stickler to the rules. so basically right now we have a vehicle behind us and of course the driver doesn't like driving so slow. peter: uh-huh. it seems to do a little meandering in the lane. is that a fair assessment? raj: it could be better, yes.
peter: but it's reading constantly. raj: yes. this is a curvy, winding road. peter: uh-huh. raj: so i'm not controlling the steering or the brake pedal or the gas pedal and it was able to shift transmission by itself. peter: i see that. this is a curvy, winding road. now there's a biker? it sensed that? raj: yes. peter: all right. how far have you come in 30 years? raj: we have come a very long way, but still some ways to go to basically completely remove the human from driving a car. peter: is this vehicle
constantly learn something? raj: this vehicle is not constantly learning but it's collecting data and using the data to teach the software about new features and functions. so it is not learning how to actually drive. it's learning after the fact. peter: how did it know there's a stop sign there? raj: the map basically has indications about where the stop line is. it did it all by itself. peter: that was the car that did that? raj: the car did it all by itself, yes. peter: it wasn't sure of its speed? raj: basically saw those parked cars. in the interest of time i do need to get back so i will take over manually. i'll just push this down. the vehicle has gone back to manual mode. >> autonomous ready. raj: it says autonomous ready. peter: and can you do that on the fly? raj: yes.
you can switch back and forth seamlessly. peter: and it's seeing all of these things? raj: yes. this crosswalk is not on the map. it understands to wait for this lady. peter: oh, ok. raj: these lanes have been changed recently. peter: ok. so it's not quite ready to be sent out on a road it's never been on before. raj: we have done that on highways. highways, we've never been on before. in open areas you have pedestrians, cyclists, more things. we do that on the highway, not in open corridors. peter: ok. a bike.
raj: i'll zoom and you can see it better. so we are back on that curvy, winding road. peter: can it read signs? raj: it can read some signs, yes, but not all signs. there are thousands of distinct signs. it does not understand all of them. so now we see that red light well. the green is the path it wants you to take. the red line is exactly on top of that.
peter: how far have you driven in this car autonomously? raj: we have driven a total of about 20,000 miles autonomously. peter: what's the longest trip you've ever taken? raj: we've done a couple hundred miles on highways. to technology has been used basically drive from san francisco to new york city, about a 3500-mile journey and the vehicle drove itself on highways about 98.6% of the time. the technology had been used -- so highways are not a problem. >> autonomous ready. raj: so, you have taken your first ride in an autonomous car.
peter: when will we do this regularly as consumers? raj: simple question, basic question, and i'll give you a long and complex answer. you can already buy vehicles, for example, tesla with an auto pilot feature. the vehicle can drive itself, but the human must be paying attention. general motors next year will introduce a similar feature they call super cruise, where the vehicle can steer itself and apply the brakes and the gas pedal as well and that will be in a cadillac sometime next year. and many high-end vehicles can already drive themselves today. so, some of these features are already available on the market . then three to five years from now, we expect that the vehicles will be able to drive themselves , but in well-specified, well-defined geographically constrained regions.
that is called geofencing. basically, for example, where bicyclists are not allowed and there is no heavy rain or heavy snow. so come in california. so some of these technologies were deployed earlier but when when you asked about when the human not drive at all? that basically implies that the technology should be able to drive the vehicle itself from any point a to any point b that you and i and other experienced drivers can drive in the u.s. that capability is going to take at least 10 years. we have come a pretty long way over the past couple of decades or so but still a ways to go before the human can take themselves out of the drivers seat and go to the back seat and take a nap. peter: have you allowed your kids and your wife to ride with you in the autonomous car? raj: sure, we've allowed family
members to go a long. many of the people from the project, yes. peter: i was a little surprised that we didn't have to sign a release before we got in. raj: i guess if you were with a corporation, but just because we are researchers. peter: why are we talking to you about autonomous cars in pittsburgh rather than detroit or silicon valley? raj: that's a great question. carnegie mellon is globally well known, has a strong reputation for computer science, engineering as well as robotics. we have a robotics institute on campus. there internationally recognized and they have more than 100 researchers in it, excluding students, if you will, and they're all extremely knowledgeable about robotics and
ages in the field have been built at c.m.u. since the early 1980's. in fact, we at carnegie mellon believe that we are the birthplace of autonomous technology dating back to about 1983 or so. a couple of years back in 2014, we literally celebrated the 30th birthday of this technology on campus. peter: you said before we started this interview that computers are simultaneously very intelligent and very stupid. raj: yes, so computers are simultaneously very intelligent. they can do things that amaze us, right? they can actually react very quickly and they can make decision that a normal person finds extremely smart. how does it know they're driving at this speed and so on. they are really intelligent because they process a 360-degree view of the vehicle
with the multiple sensory data streams from lasers, radars and cameras. very intelligent, but at the same time they are stupid, if you will, because they don't really have common sense. for example, we know that when we fall down or when we basically touch fire, it hurts, and the next time you won't do it, but computers cannot make that inference. hey, i crashed into somebody last time around, next time don't do that. it will do the exact same thing unless it is programmed to do something else, specifically by a human being. peter: what's the difference between the vehicles here in the lab. the jeep, that seems to have a lot of equipment on it, and the cadillac that we road -- we rode? raj: we see two vehicles.
one is a red jeep. the other is the cadillac that we were able to demonstrate the vehicle driving itself. the vehicle on the left, the red jeep, is called nav lab 11, meaning this was created by a research laboratory at c.m.u. called nav lab, short for navigation lab, and the 11 indicates this is the 11th generation of autonomous vehicle the lab has built. run by thebeing director and mentioned in minute back. so there were 11 variations of this vehicle. the vehicle on the right is the cadillac that we were able to drive ourselves in today. that vehicle has been created by the project that i lead with support from general motors through the u.s. department of transportation as well as the national science foundation. so because of our close working relationship with g.m., we are extremely sensitive to the aesthetics of the vehicle, the interior and the exterior as
well. we try to package the technology in such a fashion that it looks very normal. it is something that gm would be proud to both design, manufacture and sell. peter: how far along are we with this technology? raj: the technology has come very rapidly in the past several years since the 2007 car. it has come very far. the 2007 challenge, basically the outcome was that 16 competed and our team from carnegie mellon won the competition. it demonstrated once and for all that the notion of a vehicle that can drive itself is longer science fiction. it demonstrated beyond a shadow of doubt it's only a question of question of when, not if. if so since then, google hired key people from carnegie mellon,
key people from stanford university, and that's how google launched its self driving vehicle project. google basically has publicized the technology, invested several hundreds of millions of dollars into the company. and then when companies like uber came into being, they have a financial economic incentive to have the vehicles drive themselves. and meanwhile the carmakers, general motors and ford in the u.s., audi, b.m.w. in europe. nissan, honda and toyota in japan. a whole bunch of chinese car makers who want to have a part in the market and one in south korea, all of them have been investing big time in this space. meanwhile, big automotive suppliers like bosh, a company in germany, as well as delphi, based in the u.s., have been
investing bigtime as well. we have investments, research and portfolios. and from technology from google, uber, apple, lyft and so on so technology is progressing very rapidly. peter: you talk about it as action, but is it competition? are they developing their own systems like you are here? raj: thanks to capitalistic forces, there is a lot of competition. this market for self driving vehicles is expected to be huge in 15, 20 years or so, so all these companies we just discussed or pushing to own big pieces of the technology if not become leaders. that's what the competition is all about. it is about establishing leadership. peter: what about the city of pittsburgh? has it been supportive? raj: the city of pittsburgh has
been a top-notch supporter of this technology. we've been driving our self-driving cadillac on the public roads of pittsburgh since 2011. the state of pennsylvania has been friendly to the technology as well. the laws of pennsylvania allows us to drive vehicles with this technology as long as there's a human licensed driver in the driver's seat and the driver can take over at any time.us to drie besides, that, the vehicle can drive itself and because there's a human in the driver's seat, the human be would be liable. peter: doctor, what's surprised to you since 2011 when you built this cadillac? raj:
peter: what's surprised to you since 2011 when you built this cadillac? raj: that we were able to build a vehicle that for the most part looks normal on the inside and outside but we were still able to nut all the equipment so the technology can be made an additional technology cal caliber. peter: what have you taught the computers or the entire system since 2011? raj: the system, the vehicle to drive itself needs to have sensors like cameras, radars and lasers. and basically needs to have motors of some kinds that steel the wheel and can emulate the braking and acceleration actions. all the data collected by the sensors have been processed by a bank of computers but all the data processing happens by software so that literally hundreds of thousands of lines
of software that goes through these data streams sends a property of commands to the steering wheel and to the pedals. peter: and all the -- raj: so all the magic at the end of the day is in the software a.i. or artificial intelligence. peter: 10 years from now are we going to look at this cadillac and go, oh this was a nice black and go, oh this was a nice black and white tv? ramona: yes, 15 or 20 years from now people will say look at how quaint that vehicle was. peter: what's the difference between an automated car and a car?d an autonomous
raj: an autonomous car is a car capable of driving itself typically using sensors and computers that are puts into the vehicle. it senses what's happening in the environment and then has computers that reacts to the data coming in and then sends local commands for steering and braking and so on. so, that is an autonomous vehichle. a connected vehicle is something that is capable of communicating with the cloud, with traffic lights that are properly equipped, with traffic vines as well as other vehicles. your smartphones, laptops and desktops can communicate with each other. if they can, why can not a vehicle? it can. it can communicate with the environment. so a connected car is capable of you know indicating wirelessly to others in the environment. telling where it is, who the, what it plans to do and similarly wires other information can be received wirelessly so it can generate a warning to the human driver so
if the human season not able to see, for example, a strong vehicle like in the dark. the wireless communication will let the human know that there's a problem up ahead, slow down. that the roads are slick, slow down. studies indicate that up to 80% of accidents can be prevented by using this technology.
it can be generating warnings and alerts to what's human but it's possible you can actually combine the two. a connected autonomous vehicle so there you get the benefits of both, connected and automation. peter: would that take a big investment in u.s. infrastructure, to get connected cars on the road? raj: great question. it basically requires a small, by wi-fi-like device that sends messages. they basically cost about $100 each.
very, very inexpensive and it can go out as far as 600 meters so for $100, you see much farther and you can literally see -- as well because a radio wireless base can bounce on buildings and come to you as well so it gives you this super human mission, if you will. in the u.s., each state has its own jurisdiction. they can come up with their own local laws that operate within the state. you get a license from the state that you can drive. when you have a license from pennsylvania, you can also use the same license for driving in ohio and california. the states at the end of the day have the final say. if each state comes up with its own rules and regulations for automated vehicles, it would be a complete nightmare for car manufacturers. once you cross the state border, you lose supplies. the national highway administration is looking to provide a set of guidance, if
you will, to all the 50 states so they can be harmonized so if i can operate in one state, hopefully the same technology can be used as it is in the neighboring states. peter: professor rajkumar, you've put maybe 20,000 miles on driverlessly. have you gotten to the point where you'll look away from windshield wile it's driving. >> yes, when we accumulated that 20,000 miles. it so happens when we do demonstrations, sometimes public, sometimes it. and with a camera watching me off the time and then i take my eyes off the road or any hands off the wheel, they get it and highlight it. so that happens subconsciously, yes. peter: what's the main reaction you get from people riding in the car with you? raj: most if not all people who are riding in a driverless car
for the first time, the typical reaction is one of anxiety and angst. here and occasionally panic attacks but then they basically watch that the vehicle is able to drive, exactly stopping when it should stop. it's actually taking the road fairly comfortably and they build a degree of confidence. they are watching the vehicle very intently. what is it doing? after a while they say -- a few more minutes go by, i start conversing with e.p.a. other people in the car and after a
while i stop noticing what the car is doing. this takes anywhere between five and 15 minutes. so the concern that researchers like me have is not that people are fearful. the concern that i have is that people become too comfortable too quickly. so the human still needs to be alert and pay attention. peter: it seems all of a sudden all of this technology is kind of whooshing towards us. is that just a perception because of the media? raj: because of the huge market potential that exists for self-driving vehicles, many companies or many destroys are interested. number two, thanks to advances made, people know that the technology is viable.
everybody wants to carve a niche to basicallys benefit economically from that so that is a significant amount of investment on the technology side and there's basically a lot of aggressive marking so to bet on a particular piece of technology and stuff. so the potential for economic gains in the how much and the market -- is basically what you're seeing today. peter: what about computers privacy? raj: because there are different computers and hundreds and thousands of software corps we have to be cognizant of and be trolling ofpossible the technolog.
these could include cybersecurity attacks, where i could send information out and i could also receive back in. those points become potential portals of attack. so we need to be careful. whether the attack comes from across the street, the continue, the country or globally. one also has to be worried about what can be done in the physical context. for example, you can jam g.p.s., you can possibly spoof g.p.s. even a simple laser device you can use very simple so that cybersecurity and that also physical attacks that are possible -- so we elected to combine the two and basically refer to them as
cyber-physical security problems. peter: finally, doc, what's the next generation? are you working on the next generation of technology for this? raj: yes, i think of the first generation as being -- 2007, then it was conducted. they all had very similar sensors, if you will. light out on the roof of the car being an example. the cadillac you see behind me. think of as salvation two. the next genres is smog we're focusing on. use automobiles to create technologies completely. they will be able to deal with a lot more scenarios on roads and able tould also be roads that they've
never seen before. peter: what's your biggest frustration with this technology? raj: i guess there's been -- it's been very safe, so it's not that i have many frustrations. i don't call it a frustration but it's the challenge of dealing with the inherent silliness of a computer. what is obvious and basic and silly to a human needs to be taught painstakingly to a computer, so that takes time. peter: raj rajkumar of carnegie mellon. thank you for your time. raj: it's been a pleasure to talk to you, peter. >> next week, "the communicators" looks at connected cars at a research location in michigan. if you'd like to see some of our previous "the communicators" programs, go to c-span.org. announcer: the new congress starts tuesday.
watch the opening day event and activities on c-span. we are live from the u.s. capitol starting at 7am eastern. you'll meet new representatives and hear from returning members. gavels in at noon. opening day business includes the election of the house speaker, his address to the whole house and debate and a vote on rules for the new congress. one rule in particular is getting attention, a proposal to fine members who live stream video from the house floor, in response to last summer's democratic sit-in, streamed by several democrats. on c-span2 the live coverage of the senate starts at noon eastern and includes the swearing in of senators. opening day continues on c-span3. with live coverage of the ceremonial swearing-in of members of congress. at 1:00p.m. eastern, vice president joe biden presides over the swearing in of senators. we'll have a full replay of opening day.
8:00 p.m. eastern on c-span and c-span2. on tuesday, the congressional black caucus will hold a swearing-in ceremony. you will be able to watch it live starting at 9:00 a.m. eastern on c-span two. covering policy for a natural know journal. -- national journal. thank you. the headline, democrats plan to pick their battles with the donald trump. explain. guest: democrats are in a period of mourning given the elections and election of trump as they do not have either chamber. analogy.eria
let's say you're in a cafeteria a you are unhappy with a you do not want to eat something and maybe you can find a couple of things you want to choke down. will send the democratic strategy with the incoming trump administration. the republicans who will be calling the shots. democratsalk about about compromise, you hear about infrastructure is one thing. there might be a couple of other small things. will see strong democratic opposition right out of the gate. obamacare, unified democratic opposition to that. depending on what the infrastructure package looks like, that the be an area of some overlap. toocrats have been trying sort of do infrastructure spending for quite a long time and quite unsuccessfully. havees schumer and others said they are open to the concept. if you look at the early signals
from the incoming administration, they want to have some type of largely private-sector initiative around tax credits for creation of private sector jobs. i think there would be pushed back. returnsul ryan as he following the election returns back in november's from reporters about what to expect when the new congress convenes on tuesday. house speaker ryan: welcome to of a new- dawn republican party. a government focused on turning president-elect trump's victory into real progress for the american people. our team is excited and we cannot wait to get to work. we recognize that task ahead of us is enormous. if we put our country back on the right track, we have to be bold and goal bit. this country is expecting no less. in the days and weeks ahead, we will work closely with the president-elect and his transition team to put out our
ambitious plan. --t seems led by mike pence that team is led by mike pence and we are working hand in glove from the start and want to make sure we hit the ground running to deliver on the president's new agenda. better days lie ahead for our country. tot: he was reelected another term. how unified will the republican party be with the donald trump? guest: we will see less friction within the hubble the party right out of the get -- we will see less friction within the republican party right out of the gate. the most hard-core republicans, what they wanted for the past several years was a stronger, firmer stance and aggressive posturing toward president obama. they have a the same party. scissors some real with a both parties that we can see going forward.
one of the things that are trump made a hallmark was unlike many republicans he does not necessarily want to go after long-term and title programs. -- entitlement programs. that is something speak ryan has been aggressive about wanting to privatize elements of medicare. that could be one area of tension. in the democratic ranks, you have divisions on the house and senate side. on the senate, grassroots energy with democrats, the bernie .anders, elizabeth warren wing the 2010 map for senate democrats is brutal. there defending 20 56 including a bunch that trump won by 20 points or more, west virginia, .orth dakota, joe manchin they will be up for reelection. the trick for the democrats